tag:blogger.com,1999:blog-6710487119650146215.post7132514397911690982..comments2018-02-16T02:45:47.656-07:00Comments on R Tutorial Series: R Tutorial Series: Hierarchical Linear RegressionJohnhttp://www.blogger.com/profile/05331039307550313006noreply@blogger.comBlogger7125tag:blogger.com,1999:blog-6710487119650146215.post-36803272739300961542014-10-02T03:16:31.700-07:002014-10-02T03:16:31.700-07:00First, thanks for the tutorial.
Good to know that ...First, thanks for the tutorial.<br />Good to know that I did go in the right direction. But I have a question: With non-complete data I have the problem that I can not do it this way because each regression model than have different cases excluded because of the different missing patterns. So is there a way, besides multiple imputation, to compare different models in a hierachic regression with non-complete data?<br />Thanks for any comments.<br />emotionsloshttps://www.blogger.com/profile/07510857757112169855noreply@blogger.comtag:blogger.com,1999:blog-6710487119650146215.post-19430306939267247392012-06-27T08:22:04.262-07:002012-06-27T08:22:04.262-07:00The comments above refer to the title of post, whi...The comments above refer to the title of post, which was originally wrong, and not to the content.<br /><br />I disagree about your thought that this is like stepwise regression. In HLR, the researcher decides upon the order of a few variables and examines them sequentially in a few models. In stepwise regression, a computer iterates through all possible variable combinations in every model. If you search Google on this topic and you will find similar, but more extensive comparisons.John Quickhttps://www.blogger.com/profile/05331039307550313006noreply@blogger.comtag:blogger.com,1999:blog-6710487119650146215.post-60463913384681724892012-06-26T21:37:09.291-07:002012-06-26T21:37:09.291-07:00Agree with the comments above. This seems to be ma...Agree with the comments above. This seems to be manual approach to step-wise regression which has numerous problems.Anonymousnoreply@blogger.comtag:blogger.com,1999:blog-6710487119650146215.post-59655606350070355942010-07-09T08:54:33.389-07:002010-07-09T08:54:33.389-07:00Thanks for the comments. I updated the tutorial to...Thanks for the comments. I updated the tutorial to reflect the appropriate title.John M. Quickhttps://www.blogger.com/profile/05331039307550313006noreply@blogger.comtag:blogger.com,1999:blog-6710487119650146215.post-88815842328469459842010-07-09T05:23:57.134-07:002010-07-09T05:23:57.134-07:00Indeed, you are discussing what is known as &quot;...Indeed, you are discussing what is known as &quot;Hierarchical regression&quot;. The term &quot;Hierarchical linear modeling&quot; (or HLM) is used for multilevel models and using that as a title for this part is confusing.<br />Apart from that, it is nicely done.Anonymousnoreply@blogger.comtag:blogger.com,1999:blog-6710487119650146215.post-85154809334156670342010-07-03T06:06:48.142-07:002010-07-03T06:06:48.142-07:00Just a doubt:
Your title &quot;Hierarchical linea...Just a doubt:<br /><br />Your title &quot;Hierarchical linear modeling&quot; is suggestive of mixed modeling/HLM/MLM literature (used for clustered/non-independent data), and not the hierarchical regression (based on analyzing hierarchical Anova models) that you actually seem to be explaining here. <br /><br />Maybe my mistake (i AM a novice), but if what i say is true, i guess it may be better to correct this and restate the title as &quot;Hierarchical regression&quot;; otherwise new-comers interested in mixed modeling might mistake the message.<br /><br />Bye,take care.Anonymousnoreply@blogger.comtag:blogger.com,1999:blog-6710487119650146215.post-36574639238953069912010-06-25T02:19:47.281-07:002010-06-25T02:19:47.281-07:00How do handle categorical independent variables in...How do handle categorical independent variables in HLM?Anonymousnoreply@blogger.com